Maximum likelihood identification of glint noise

Wen-Rong Wu*

*Corresponding author for this work

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

If the non-Gaussian distribution function of radar glint noise is known, the Masreliez filter can be applied to improve target tracking performance. We investigate the glint identification problem using the maximum likelihood (ML) method. Two models for the glint distribution are used, a mixture of two Gaussian distributions and a mixture of a Gaussian and a Laplacian distribution. An efficient initial estimate method based on the QQ-plot is also proposed. Simulations show that the ML estimates converge to truths.

Original languageEnglish
Pages (from-to)41-51
Number of pages11
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume32
Issue number1
DOIs
StatePublished - 1 Dec 1996

Fingerprint Dive into the research topics of 'Maximum likelihood identification of glint noise'. Together they form a unique fingerprint.

  • Cite this